Chuang Wen-Ching, Gober Patricia
School of Sustainability, Arizona State University, Tempe, Arizona, USA.
Environ Health Perspect. 2015 Jun;123(6):606-12. doi: 10.1289/ehp.1307868. Epub 2015 Jan 30.
Vulnerability mapping based on vulnerability indices is a pragmatic approach for highlighting the areas in a city where people are at the greatest risk of harm from heat, but the manner in which vulnerability is conceptualized influences the results.
We tested a generic national heat-vulnerability index, based on a 10-variable indicator framework, using data on heat-related hospitalizations in Phoenix, Arizona. We also identified potential local risk factors not included in the generic indicators.
To evaluate the accuracy of the generic index in a city-specific context, we used factor scores, derived from a factor analysis using census tract-level characteristics, as independent variables, and heat hospitalizations (with census tracts categorized as zero-, moderate-, or high-incidence) as dependent variables in a multinomial logistic regression model. We also compared the geographical differences between a vulnerability map derived from the generic index and one derived from actual heat-related hospitalizations at the census-tract scale.
We found that the national-indicator framework correctly classified just over half (54%) of census tracts in Phoenix. Compared with all census tracts, high-vulnerability tracts that were misclassified by the index as zero-vulnerability tracts had higher average income and higher proportions of residents with a duration of residency < 5 years.
The generic indicators of vulnerability are useful, but they are sensitive to scale, measurement, and context. Decision makers need to consider the characteristics of their cities to determine how closely vulnerability maps based on generic indicators reflect actual risk of harm.
基于脆弱性指数的脆弱性映射是一种务实的方法,用于突出城市中人们受高温伤害风险最大的区域,但脆弱性的概念化方式会影响结果。
我们使用亚利桑那州凤凰城与高温相关的住院数据,对基于10变量指标框架的通用国家高温脆弱性指数进行了测试。我们还确定了通用指标中未包含的潜在本地风险因素。
为了评估通用指数在特定城市背景下的准确性,我们在多项逻辑回归模型中,将通过使用普查区层面特征进行因子分析得出的因子得分作为自变量,将高温住院情况(普查区分为零发病率、中等发病率或高发病率)作为因变量。我们还在普查区尺度上比较了从通用指数得出的脆弱性地图与从实际高温相关住院情况得出的脆弱性地图之间的地理差异。
我们发现,国家指标框架正确分类了凤凰城略多于一半(54%)的普查区。与所有普查区相比,被该指数错误分类为零脆弱性普查区的高脆弱性普查区平均收入更高,居住时间<5年的居民比例更高。
通用的脆弱性指标是有用的,但它们对尺度、测量和背景敏感。决策者需要考虑其城市的特征,以确定基于通用指标的脆弱性地图在多大程度上反映了实际的伤害风险。